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---
license: mit
base_model: xlm-roberta-large
tags:
- generated_from_trainer
datasets:
- masakhaner2
metrics:
- f1
model-index:
- name: xlm-roberta-large-finetuned-wolof
results:
- task:
name: Token Classification
type: token-classification
dataset:
name: masakhaner2
type: masakhaner2
config: wol
split: validation
args: wol
metrics:
- name: F1
type: f1
value: 0.8361858190709046
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# xlm-roberta-large-finetuned-wolof
This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the masakhaner2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3771
- F1: 0.8362
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.7475 | 1.0 | 739 | 0.4053 | 0.6989 |
| 0.3252 | 2.0 | 1478 | 0.3251 | 0.6653 |
| 0.1983 | 3.0 | 2217 | 0.3703 | 0.8234 |
| 0.1139 | 4.0 | 2956 | 0.3170 | 0.8299 |
| 0.052 | 5.0 | 3695 | 0.3771 | 0.8362 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
|